It is true that Data analytics is the talk of the town, with major industries like healthcare, sports, education, government, etc. adopting data analytics, you got to know what and why? So let’s begin with understanding the basics.
What is Data Analytics? It is a field of analyzing raw, unstructured, and massive volumes of data in order to draw insights, patterns, trends, and conclusions, and that help in decision-making.
When we talk about Data, it is a must to know that it is an important business asset. Today innovation takes place only because it is the data analysis that helps firms to have a competitive edge in the global market. With the help of Big Data and Artificial Intelligence, data analysis has become more advanced, fast, and accurate. Providing users with AI-based analytics tools will enable them to drive high-quality insights and details from the data. This will not only benefit the organization but will also create data literacy among the employees.
You might be wondering how is AI used in Data Analytics and why so many companies are adopting it. The use of AI in Data analytics are proved to be a game-changer and here’s why, AI makes analytics simpler, it helps in data modeling, data visualization, automating data, enhancing data visualization, gaining insights on events, issues, trends, people, and carrying out several other analytics tasks that could be time-consuming and labor-intensive. It has enabled companies to save time, and energy.
AI can identify various types of data, find patterns and connections, and recognize knowledge by using language processing. It helps in data exploration and preparation of data models. Since AI is deep learning and machine learning-based, it can learn error patterns and flaws in the data. It can alert data users about unexpected data patterns, constantly monitor several events, and abnormalities, and identify potential and existing threats if any in the data. AI-based analytics is a cost-cutting technology that enabled so many businesses to become effective and make the right decisions.
Types of Data Analytics
Data analytics are of different types as well, every type is unique in its own way.
Descriptive Analytics
This type of analytics is used when they are used for the interpretation of historical data. This enables them to better understand, what changes have occurred in the business. It summarizes and highlights patterns in historical and current data, then enables businesses to draw comparisons. For example, Descriptive analytics is used to keep a tab on KPIs such as year-to-year profits earned, sales growth, customer satisfaction, etc.
Diagnostic Analytics
This type of Data analytics is an advanced form of analytics that delves deeper into the data to understand why did this happen and what is the outcome. It provides a deeper analysis of this question. It is again related to analyzing historical information but at a deeper level than descriptive analytics. For example, the HR department is looking for the right candidate for a job post, for this, they will compare performance in accordance with the position he is applying for.
Predictive Analytics
This type of Data analytics is that predicts future events on the basis of past behavior. It makes use of data, statistical algorithms, machine learning, data mining, etc, that helps in predictive models that are used for forecasting the likely events of the future. For example, it can be used to predict the buying behavior of the retail sector.
Prescriptive Analytics
This type of Data analytics analyzes the data and provides recommendations to businesses to improve their decision-making. It can be used to make any type of decision and of any duration, from immediate to long-term. It also makes use of descriptive and predictive analytics to generate recommendations. For example, the Marketing department have to access a large volume of customer data that can help to devise suitable marketing strategies such as what customers want in the products, what price they are willing to pay, etc.
Data Analytics Tools
You must be wondering, how analytics of data actually happen, here are some famously used tools by top companies.
Microsoft Power BI
It is a top business analytics service, it provides visualization, and business intelligence capabilities. It is a data exploration and reports authoring tool. Helps to view reports, dashboards, etc. Helps to build automated machine learning models.
Qlik
It is a software and analytics tool that specializes in providing data visualization, self-service business intelligence products, and an executive dashboard. The tool boasts strong support for data exploration, and provides customization.
SAP Business Objects
It is a software company that specializes in business intelligence. It provides self-service analytics, provides a flexible platform. Many companies find it worth the price because of its versatility.
Google Data Studio
It is a dashboard and data visualization tool from Google. It automatically integrates other tools by Google such as Google Analytics, Google Ads, and Google Big Query. Data Studio can work very well with data provided from other sources as well.
Periscope Data
It is owned by Sisense, a business intelligence software that allows users to keep an interactive data dashboard. Functionalities include scorecards, data warehousing, data mining, and predictive analytics. Technical analysts transform data using SQL, Python, or R and proceed to create and share dashboards.
IBM Cognos
It is also a business intelligence platform that includes built-in AI tools. The AI tools reveal and explain hidden data. Apart from that it toolset for reporting, analytics, modeling, monitoring events, and metrics.
Redash
It is an open-source tool for companies to query, visualize and collaborate. It is a cost-effective tool for querying data and building visualizations.
Jupyter Notebook
It is an open software company, an interactive web tool even called a computational notebook. Many researchers use this to combine software code, computational output, explanatory text, and multimedia resources in a document.
Top Data Analytics Courses.
Data Analytics is a lucrative career and is currently in high demand and offers attractive pay packages. If you want to start a career in data analytics here are some top data analytics courses with Global Accreditation, most of these courses are offered by Coursera.
- Google: Google Data Analytics
- University of Pennsylvania: Business Analytics
- University of Colorado Boulder: Advanced Business Analytics.
- IBM Data Analytics
- IBM Data Analyst
- IBM Analysis and Visualization Foundations
- John Hopkins University: Data Science
- IMB Data Science
- University of California: Data Visualization with Tableau
- University of Michigan: Applied Data Science with Python
For more details please visit,
Top Data Analytics Courses – Learn Data Analytics Online | Coursera
In conclusion, Data Analytics is one of the most demanding careers in the 21st Century, it is expected to completely change the way we live or do business. We are still at quite an early stage of the data era, who knows what all discoveries are yet to be tapped? But if you start a career in this field there’s a lot of scope in this field. So go ahead and start your journey!
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